Tech Chat: From SingleCore to MultiCore with Jeronimo Castrillon-Mazo - MES031

Mar 15, 2016

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Tech Chat: From SingleCore to MultiCore with Jeronimo Castrillon-Mazo

Today it’s up to Jeronimo Castrillon-Mazo. We got acquainted at the Embedded World 2016 in Nuremberg. He is co-founder and adviser at Silexica. They have won the Embedded Award 2015 in the Tools-category for SLX MultiCore Toolsuite. That drives me to visit their booth. Having an amazing talk I asked Jeronimo to appear in this podcast. Let’s have some tech-chat, widen the topic and enlarge the audience for this interesting topic.

Jeronimo has studied Electrical Engineering in Colombia, achieved his Master-degree at ALaRI-institute in Lugano, Switzerland. He has made his Ph.D. 2013 at the well known RWTH Aachen. In 2014 Jeronimo joined the department of computer science of the TU Dresden as professor for compiler construction. He has a proven track record of multi- and many-core programming. Moreover he is known as specialist within the realm of automatic code generation.

Nowadays we have tons of single-core based legacy code. In parallel multicore hardware platforms have overtaken. Usually software for multicore needs to be designed manually. What might happen if the amount of cores still increases in future? How shall we handle existing code bases? Migrate all of them manually? Or might there be automatica ways to move towards multicore structures? And how can we improve software design for multicore deployment? For all of that the SLX MultiCore Toolsuite’s solutions will support.

We’re discussing the benefits a tool has instead of redesigning code manually for multicore systems. We dive into the models and operations necessary to paralellize existing code. We identify user-stories and we mention tricky pitfalls. Jeronimo unveils details of automatic code-analysis and problems solved to provide a tool like SLX MultiCore.

Stay with me and enjoy the chat.

Essential Answers Provided In This Episode For:

What stands the SLX Multicore Toolsuite stands for?
When does the attempt to parallelize do not make much sense?
What kind of applications and languages are supported by SLX?
Who are the 3 different kind of users?
What different models are in use to support our migration from single- to multi-core?
How do we handle and prevent race-conditions?
How does Silexica prevent resource bottlenecks created by parallelism?
What are the general benefits of using a tool like SLX?
And much much more.

Selected Links and Resources From This Episode

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